Estimating the Initial Pressure, Permeability and Skin Factor of Oil Reservoirs Using Artificial Neural Networks
عنوان مقاله: Estimating the Initial Pressure, Permeability and Skin Factor of Oil Reservoirs Using Artificial Neural Networks
شناسه ملی مقاله: NICEC10_358
منتشر شده در دهمین کنگره ملی مهندسی شیمی ایران در سال 1384
شناسه ملی مقاله: NICEC10_358
منتشر شده در دهمین کنگره ملی مهندسی شیمی ایران در سال 1384
مشخصات نویسندگان مقاله:
Jeirani - Chemical Engineering Department, Shahid Bahonar University of Kerman, Kerman, Iran
Mohebbi - Chemical Engineering Department, Shahid Bahonar University of Kerman, Kerman, Iran
خلاصه مقاله:
Jeirani - Chemical Engineering Department, Shahid Bahonar University of Kerman, Kerman, Iran
Mohebbi - Chemical Engineering Department, Shahid Bahonar University of Kerman, Kerman, Iran
Artificial neural network, a biologically inspired computing method which has an ability to learn, self-adjust, and be trained, provides a powerful tool in solving pattern recognition problems. In this study, a new approach based on artificial neural networks (ANNs) has been designed to estimate the initial pressure, permeability and skin factor of oil reservoir using the pressure build up test data. Five sets of actual field data in conventional and dual porosity reservoirs have been used to test the results of the neural network. The results from the network are in good agreement with the results from Horner plot. Finally, it is shown that the application of artificial neural networks in a pressure build up test reduces the cost of the test and it is also a valuable tool for well testing.
کلمات کلیدی: Artificial neural networks; Initial pressure; Permeability; Skin factor; Pressure build up test; Well test
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/23595/